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Using AI for Abnormal Behavior Detection

017286889e25c87cb44b20ceca2d1d79?s=47 Daron Yondem
November 14, 2019
Technology
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45

Using AI for Abnormal Behavior Detection

This is a presentation I used during my talk at the IT Summit Turkey 2019.

017286889e25c87cb44b20ceca2d1d79?s=128

Daron Yondem

November 14, 2019
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Transcript

  1. Daron Yöndem http://daron.me @daronyondem

  2. • Out of the Box Anomaly Detection for Cloud Apps

    • Anomaly Detection in the world of IoT • Anomaly Detector for Everyone

  3. • Risky IP address • Login failures • Admin activity

    • Inactive accounts • Location • Impossible travel • Device and user agent • Activity rate

  4. • Entity behavioral analytics (UEBA) • Machine learning (ML)

  5. None
  6. None

  7. • Azure IoT Edge, Azure Stream Analytics offers built-in machine

    learning based anomaly detection • AnomalyDetection_SpikeAndDip and AnomalyDetection_ChangePoint

  8. An AI service that helps you foresee problems before they

    occur
  9. None
  10. None
  11. None
  12. None
  13. None

  14. Microsoft Cloud App Security Product Page https://drn.fyi/375O6ML Anomaly Detection with

    Azure Stream Analytics and ML https://drn.fyi/33ZlpPu Online Playground for Anomaly Detector https://drn.fyi/2Qhqz5C Azure Anomaly Detector Video https://drn.fyi/2CHyl0z

  15. http://daron.me | @daronyondem Download slides here; http://decks.daron.me